Genome-wide SNP discovery and core marker sets for assessment of genetic variations in cultivated pumpkin (Cucurbita spp.)

Abstract

Three pumpkin species Cucurbita maxima, C. moschata, and C. pepo are commonly cultivated worldwide. To identify genome-wide SNPs in these cultivated pumpkin species, we collected 48 F 1 cultivars consisting of 40 intraspecific hybrids (15 C. maxima, 18 C. moschata, and 7 C. pepo) and 8 interspecific hybrids (C. maxima x C. moschata). Genotyping by sequencing identified a total of 37,869 confident SNPs in this collection. These SNPs were filtered to generate a subset of 400 SNPs based on polymorphism and genome distribution. Of the 400 SNPs, 288 were used to genotype an additional 188 accessions (94 F 1 cultivars, 50 breeding lines, and 44 landraces) with a SNP array-based platform. Reliable polymorphisms were observed in 224 SNPs (78.0%) and were used to assess genetic variations between and within the four predefined populations in 223 cultivated pumpkin accessions. Both principal component analysis and UPGMA clustering found four major clusters representing three pumpkin species and interspecific hybrids. This genetic differentiation was supported by pairwise F st and Nei's genetic distance. The interspecific hybrids showed a higher level of genetic diversity relative to the other three populations. Of the 224 SNPs, five subsets of 192, 96, 48, 24, and 12 markers were evaluated for variety identification. The 192, 96, and 48 marker sets identified 204 (91.5%), 190 (85.2%), and 141 (63.2%) of the 223 accessions, respectively, while other subsets showed <25% of variety identification rates. These SNP markers provide a molecular tool with many applications for genetics and breeding in cultivated pumpkin.

Development of a core set of single nucleotide polymorphism markers for genetic diversity analysis and cultivar fingerprinting in cowpea

“…We also found that the 75 cultivars were distinguished completely when the 43rd SNPs were added, indicating that the discriminatory power of the core SNPs increased along with the number of SNPs used. This phenomenon was also found in pumpkin, where the 96, 48, 24, and 12 core SNP sets were able to identify 85.2%, 63.2%, 24.2%, and 4.9% of the 223 pumpkin accessions, respectively (Nguyen et al, 2020), again indicating a positive correlation between the germplasm discrimination power and the core SNP number. For each cultivar, the genotypes of the 50 core SNPs can be used for their unique DNA fingerprint or applied for rapid seed purity tests.…”

“…However, there is a large gap between the development of SNP markers and their application in practical breeding processes because SNP genotyping requires complex detection technologies and has high costs. Recently, multiple cost‐effective and flexible core SNP sets based on the KASP technology have been developed in rice, Brassica rapa , pepper and pumpkin (Du et al, 2019; Li et al, 2019; Nguyen et al, 2020; Yang et al, 2019). With high representation and resolution, core SNP sets have been widely used in genetic diversity analysis, marker‐assisted selection, and seed intellectual rights protection.…”

“…Compared with the reported core SNP set from resequencing, such as genotyping by sequencing (GBS) in other crops (Du et al, 2019; Nguyen et al, 2020), the core SNP set in our study was directly derived from the existing Cowpea iSelect Consortium Assay. A total of 40,089 high‐quality primers, with a 78.4% conversion rate, were obtained from the 51,128 SNPs, which is close to the 81.5% conversion rate in maize (Semagn et al, 2014).…”

Genome-Wide Association Studies for Striga asiatica Resistance in Tropical Maize

“…Classical markers are less preferred by breeders because they are less polymorphic and are highly influenced by the environment as well as influenced by the plant growth stage [4]. Molecular markers such as single-nucleotide polymorphism (SNP) markers are the most ideal to use in markerfacilitated breeding because they are codominant, uniformly distributed throughout the genome, highly reproducible, and highly polymorphic [6]. The genome-wide association study (GWAS) is a modern technique used to detect connotation between genetic variants and traits in samples from populations mainly based on SNP markers [7].…”

Genetic Mapping and Identification of the Candidate Gene for White Seed Coat in Cucurbita maxima

“…Molecular markers including random amplified polymorphic DNA (RAPD), amplified fragment length polymorphism (AFLP), simple sequence repeat (SSR), and single-nucleotide polymorphism (SNP) have been developed to construct genetic linkage map in Cucurbita [ 33 , 34 , 35 ]. Improvements of whole genome sequences and high-density genetic maps have promoted the precision of genomic data in Cucurbita and support a better foundation for the research and application of candidate genes in Cucurbita species [ 36 , 37 , 38 , 39 , 40 , 41 ]. With effective utilization of molecular markers and genetic map resources, QTLs for many agronomic traits and candidate genes have been identified and applicated accordingly in breeding selection [ 42 , 43 , 44 , 45 , 46 ].…”